Name
Abstract | ||
|---|---|---|
Reference texts such as encyclopedias and news articles can manifest biased language when objective reporting is substituted by subjective writing. Existing methods to detect bias mostly rely on annotated data to train machine learning models. However, low annotator agreement and comparability is a substantial drawback in available media bias corpora. To evaluate data collection options, we collec... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/JCDL52503.2021.00053 | 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) |
Keywords | DocType | ISSN |
Crowdsourcing,Training,Data integrity,Machine learning,Encyclopedias,Media,Writing | Conference | 2575-7865 |
ISBN | Citations | PageRank |
978-1-6654-1770-9 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Timo Spinde | 1 | 0 | 3.38 |
| David Krieger | 2 | 0 | 0.34 |
| Manuel Plank | 3 | 0 | 0.34 |
| Bela Gipp | 4 | 0 | 0.34 |